Recursive Dynamic Modelling in Changing Operating Conditions

Esko K. Juuso
Control Engineering Group, Faculty of Technology, University of Oulu, Finland

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp15119169

Ingår i: Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56), October, 7-9, 2015, Linköping University, Sweden

Linköping Electronic Conference Proceedings 119:17, s. 169-174

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Publicerad: 2015-11-25

ISBN: 978-91-7685-900-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Changing operating condition may require updates for the dynamic models. Recursive updates are needed when there are not sufficient information about the new situations. In machine diagnostics and prognostics, the analysis starts from good conditions and new phenomena, which activate with time, may change considerably the model. In biological wastewater treatment processes, the condition of the biomass changes drastically the dynamic operation of the treatment process. Direct measurements of the biomass condition are under development. Recursive modelling is clearly needed in these situations. The usual approachis to modify the model equations. However, the interactions do not necessarily change if the meanings of the variables are modified. This paper keeps the the model equations constant and modifies the nonlinear scaling of the variables by extending the data-driven scaling to recursive approach. The recursive methodology is tested in two applications: machine diagnostics and wastewater treatment.


intelligent modelling; recursive statistical analysis; adaptive modelling; prognostics; transitions


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